Sales forecasts in clothing industry: The key success factor of the supply chain management

Thomassey, Sébastien

doi:10.1016/j.ijpe.2010.07.018

Cited by 160 publications

(82 citation statements)

References 38 publications

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“…Appropriate product quality with timely availability is necessary for surviving in the ever increasing competition. The textile supply chain consists of multiple actors and the total production lead-time can be as high as 12-24 months, whereas the fashion trend changes almost every season [46]. Any delay in production or quality issues can hamper the brands severely.…”

Section: Related Workmentioning

confidence: 99%

“…Most of the textile supply chains are driven by the retailers or brand owners, who monitor the market demands and place the order for upstream suppliers [46]. A retailer generally does not own any production facilities and acts as a reseller who procures the products from the upstream suppliers and sells them to the customers [46]. Therefore, all the actors excluding the retailer are considered as B2B (business-to-business), whereas the retailer is considered as B2C (business-to-customer) as shown in Figure 1.…”

Section: Usage Requirement Of the Traceability Information In The Texmentioning

confidence: 99%

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Developing a Framework for Traceability Implementation in the Textile Supply Chain

Kumar

Hallqvist

Ekwall

2017

Systems

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Traceability has recently gained considerable attention in the textile industry. Traceability stands for information sharing about a product including the product history, specification, or location. With the involvement of globally dispersed actors in the textile supply chain, ensuring appropriate product quality with timely supplies is crucial for surviving in this industry with ever increasing competition. Hence it is of paramount importance for a supply chain actor to track every product and trace its history in the supply chain. In this context, this paper presents a framework to implement traceability in the textile supply chain. A system approach has been followed, where firstly the usage requirement of traceability is defined, and then a framework for implementing intra-actor or internal traceability and inter-actor or external traceability is discussed. This article further presents a sequential diagram to demonstrate the interaction and information exchange between the actors in the supply chain, when the traceability information is requested. An example is also illustrated for data storage using a relational database management system and information exchange using XML for the textile weaver. Finally, the article discusses challenges and future studies required to implement traceability in the textile supply chain.

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Section: Related Workmentioning

confidence: 99%

Section: Usage Requirement Of the Traceability Information In The Texmentioning

confidence: 99%

Developing a Framework for Traceability Implementation in the Textile Supply Chain

Kumar

Hallqvist

Ekwall

2017

Systems

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“…Many decisions are based on sales forecasting, such as purchasing, order, replenishments and inventory allocation. Accurate sales forecasts are therefore a key success factor for apparel companies [6].…”

Section: Related Workmentioning

confidence: 99%

“…This would probably be the case for social data as well. As far as stakeholders go, they rely on brokerage firms and financial information firm for forecasts 6 .…”

Section: Event Studymentioning

confidence: 99%

Forecasting Nike's sales using Facebook data

Boldt

Vinothan

Florian

et al. 2016

2016 IEEE International Conference on Big Data (Big Data)

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Abstract-This paper tests whether accurate sales forecasts for Nike are possible from Facebook data and how events related to Nike affect the activity on Nike's Facebook pages. The paper draws from the AIDA sales framework (Awareness, Interest, Desire,and Action) from the domain of marketing and employs the method of social set analysis from the domain of computational social science to model sales from Big Social Data. The dataset consists of (a) selection of Nike's Facebook pages with the number of likes, comments, posts etc. that have been registered for each page per day and (b) business data in terms of quarterly global sales figures published in Nike's financial reports. An event study is also conducted using the Social Set Visualizer (SoSeVi). The findings suggest that Facebook data does have informational value. Some of the simple regression models have a high forecasting accuracy. The multiple regressions have a lower forecasting accuracy and cause analysis barriers due to data set characteristics such as perfect multicollinearity. The event study found abnormal activity around several Nike specific events but inferences about those activity spikes, whether they are purely event-related or coincidences, can only be determined after detailed case-bycase text analysis. Our findings help assess the informational value of Big Social Data for a company's marketing strategy, sales operations and supply chain.

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“…Forecasting has been studied for fashion sales and inventory [63], although the results are usually meaningless in practice. To cope with the fast fashion feature, a practical way is to respond to it fast and efficiently.…”

Section: Responsive System For Fashionable Productsmentioning

confidence: 99%

Sustainable Rent-Based Closed-Loop Supply Chain for Fashion Products

Chen

et al. 2014

Sustainability

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Abstract:The textile and clothing industry generates much pollution and consumes a large amount of resources. Improper uses and disposal of clothing products make the problems much more severe. Fast fashion products shorten the valid lifecycle and generate more waste than regular clothing products. Considering the features of fashion products, a system of a rent-based closed-loop supply chain is developed to improve the sustainability of fashion products. The supply chain processes (fashion design and manufacturing, laundry, logistics and disposal), the operations management issues (inventory management, closed-loop logistics, human-clothing matching, booking system and the rental pricing) and the sustainability promotion aspects (customization, responsive system, culture and policy aspects) are investigated by devising sustainable strategies. The rationalities of the developed system and strategies are reviewed and elucidated in detail. The results may contribute to building sustainable closed-loop fashion supply chains, the related information systems and operational and managerial mechanisms.

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Sales forecasts in clothing industry: The key success factor of the supply chain management

Cited by 160 publications

References 38 publications

Developing a Framework for Traceability Implementation in the Textile Supply Chain

Developing a Framework for Traceability Implementation in the Textile Supply Chain

Forecasting Nike's sales using Facebook data

Sustainable Rent-Based Closed-Loop Supply Chain for Fashion Products

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